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clip-mixer-200k
bilbo991/clip-mixer-200k
clip-mixer-200k is a feature extraction model from bilbo991. Use it when you need embeddings to search or compare text. It is set up for transformers.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Task
- Feature Extraction
- Library
- transformers
- Model type
- vision-text-dual-encoder
- Access
- Public
- Created
- Aug 15, 2023
- Updated
- Aug 16, 2023
- SHA
- c82a59ab
Base models
Model card
From the Hugging Face model README
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
clip-mixer-200k
This model is a fine-tuned version of clip-mixer-200k on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 2.5681
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 5e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3.0
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 1.9911 | 1.0 | 6250 | 2.7263 |
| 1.2866 | 2.0 | 12500 | 2.5681 |
| 0.6188 | 3.0 | 18750 | 2.6770 |
Framework versions
- Transformers 4.32.0.dev0
- Pytorch 2.0.1+cu117
- Datasets 2.14.1
- Tokenizers 0.13.3
- Task
- Feature Extraction
- Library
- transformers
- Type
- vision-text-dual-encoder
- Created
- Aug 15, 2023
- Updated
- Aug 16, 2023